cpython/Doc/library/concurrent.futures.rst

:mod:`!concurrent.futures` --- Launching parallel tasks
=======================================================

.. module:: concurrent.futures
   :synopsis: Execute computations concurrently using threads or processes.

.. versionadded:: 3.2

**Source code:** :source:`Lib/concurrent/futures/thread.py`
and :source:`Lib/concurrent/futures/process.py`

--------------

The :mod:`concurrent.futures` module provides a high-level interface for
asynchronously executing callables.

The asynchronous execution can be performed with threads, using
:class:`ThreadPoolExecutor` or :class:`InterpreterPoolExecutor`,
or separate processes, using :class:`ProcessPoolExecutor`.
Each implements the same interface, which is defined
by the abstract :class:`Executor` class.

.. include:: ../includes/wasm-notavail.rst

Executor Objects
----------------

.. class:: Executor

   An abstract class that provides methods to execute calls asynchronously.  It
   should not be used directly, but through its concrete subclasses.

   .. method:: submit(fn, /, *args, **kwargs)

      Schedules the callable, *fn*, to be executed as ``fn(*args, **kwargs)``
      and returns a :class:`Future` object representing the execution of the
      callable. ::

         with ThreadPoolExecutor(max_workers=1) as executor:
             future = executor.submit(pow, 323, 1235)
             print(future.result())

   .. method:: map(fn, *iterables, timeout=None, chunksize=1)

      Similar to :func:`map(fn, *iterables) <map>` except:

      * the *iterables* are collected immediately rather than lazily;

      * *fn* is executed asynchronously and several calls to
        *fn* may be made concurrently.

      The returned iterator raises a :exc:`TimeoutError`
      if :meth:`~iterator.__next__` is called and the result isn't available
      after *timeout* seconds from the original call to :meth:`Executor.map`.
      *timeout* can be an int or a float.  If *timeout* is not specified or
      ``None``, there is no limit to the wait time.

      If a *fn* call raises an exception, then that exception will be
      raised when its value is retrieved from the iterator.

      When using :class:`ProcessPoolExecutor`, this method chops *iterables*
      into a number of chunks which it submits to the pool as separate
      tasks.  The (approximate) size of these chunks can be specified by
      setting *chunksize* to a positive integer.  For very long iterables,
      using a large value for *chunksize* can significantly improve
      performance compared to the default size of 1.  With
      :class:`ThreadPoolExecutor` and :class:`InterpreterPoolExecutor`,
      *chunksize* has no effect.

      .. versionchanged:: 3.5
         Added the *chunksize* argument.

   .. method:: shutdown(wait=True, *, cancel_futures=False)

      Signal the executor that it should free any resources that it is using
      when the currently pending futures are done executing.  Calls to
      :meth:`Executor.submit` and :meth:`Executor.map` made after shutdown will
      raise :exc:`RuntimeError`.

      If *wait* is ``True`` then this method will not return until all the
      pending futures are done executing and the resources associated with the
      executor have been freed.  If *wait* is ``False`` then this method will
      return immediately and the resources associated with the executor will be
      freed when all pending futures are done executing.  Regardless of the
      value of *wait*, the entire Python program will not exit until all
      pending futures are done executing.

      If *cancel_futures* is ``True``, this method will cancel all pending
      futures that the executor has not started running. Any futures that
      are completed or running won't be cancelled, regardless of the value
      of *cancel_futures*.

      If both *cancel_futures* and *wait* are ``True``, all futures that the
      executor has started running will be completed prior to this method
      returning. The remaining futures are cancelled.

      You can avoid having to call this method explicitly if you use the
      :keyword:`with` statement, which will shutdown the :class:`Executor`
      (waiting as if :meth:`Executor.shutdown` were called with *wait* set to
      ``True``)::

         import shutil
         with ThreadPoolExecutor(max_workers=4) as e:
             e.submit(shutil.copy, 'src1.txt', 'dest1.txt')
             e.submit(shutil.copy, 'src2.txt', 'dest2.txt')
             e.submit(shutil.copy, 'src3.txt', 'dest3.txt')
             e.submit(shutil.copy, 'src4.txt', 'dest4.txt')

      .. versionchanged:: 3.9
         Added *cancel_futures*.


ThreadPoolExecutor
------------------

:class:`ThreadPoolExecutor` is an :class:`Executor` subclass that uses a pool of
threads to execute calls asynchronously.

Deadlocks can occur when the callable associated with a :class:`Future` waits on
the results of another :class:`Future`.  For example::

   import time
   def wait_on_b():
       time.sleep(5)
       print(b.result())  # b will never complete because it is waiting on a.
       return 5

   def wait_on_a():
       time.sleep(5)
       print(a.result())  # a will never complete because it is waiting on b.
       return 6


   executor = ThreadPoolExecutor(max_workers=2)
   a = executor.submit(wait_on_b)
   b = executor.submit(wait_on_a)

And::

   def wait_on_future():
       f = executor.submit(pow, 5, 2)
       # This will never complete because there is only one worker thread and
       # it is executing this function.
       print(f.result())

   executor = ThreadPoolExecutor(max_workers=1)
   executor.submit(wait_on_future)


.. class:: ThreadPoolExecutor(max_workers=None, thread_name_prefix='', initializer=None, initargs=())

   An :class:`Executor` subclass that uses a pool of at most *max_workers*
   threads to execute calls asynchronously.

   All threads enqueued to ``ThreadPoolExecutor`` will be joined before the
   interpreter can exit. Note that the exit handler which does this is
   executed *before* any exit handlers added using ``atexit``. This means
   exceptions in the main thread must be caught and handled in order to
   signal threads to exit gracefully. For this reason, it is recommended
   that ``ThreadPoolExecutor`` not be used for long-running tasks.

   *initializer* is an optional callable that is called at the start of
   each worker thread; *initargs* is a tuple of arguments passed to the
   initializer.  Should *initializer* raise an exception, all currently
   pending jobs will raise a :exc:`~concurrent.futures.thread.BrokenThreadPool`,
   as well as any attempt to submit more jobs to the pool.

   .. versionchanged:: 3.5
      If *max_workers* is ``None`` or
      not given, it will default to the number of processors on the machine,
      multiplied by ``5``, assuming that :class:`ThreadPoolExecutor` is often
      used to overlap I/O instead of CPU work and the number of workers
      should be higher than the number of workers
      for :class:`ProcessPoolExecutor`.

   .. versionchanged:: 3.6
      Added the *thread_name_prefix* parameter to allow users to
      control the :class:`threading.Thread` names for worker threads created by
      the pool for easier debugging.

   .. versionchanged:: 3.7
      Added the *initializer* and *initargs* arguments.

   .. versionchanged:: 3.8
      Default value of *max_workers* is changed to ``min(32, os.cpu_count() + 4)``.
      This default value preserves at least 5 workers for I/O bound tasks.
      It utilizes at most 32 CPU cores for CPU bound tasks which release the GIL.
      And it avoids using very large resources implicitly on many-core machines.

      ThreadPoolExecutor now reuses idle worker threads before starting
      *max_workers* worker threads too.

   .. versionchanged:: 3.13
      Default value of *max_workers* is changed to
      ``min(32, (os.process_cpu_count() or 1) + 4)``.


.. _threadpoolexecutor-example:

ThreadPoolExecutor Example
~~~~~~~~~~~~~~~~~~~~~~~~~~
::

   import concurrent.futures
   import urllib.request

   URLS = ['http://www.foxnews.com/',
           'http://www.cnn.com/',
           'http://europe.wsj.com/',
           'http://www.bbc.co.uk/',
           'http://nonexistent-subdomain.python.org/']

   # Retrieve a single page and report the URL and contents
   def load_url(url, timeout):
       with urllib.request.urlopen(url, timeout=timeout) as conn:
           return conn.read()

   # We can use a with statement to ensure threads are cleaned up promptly
   with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
       # Start the load operations and mark each future with its URL
       future_to_url = {executor.submit(load_url, url, 60): url for url in URLS}
       for future in concurrent.futures.as_completed(future_to_url):
           url = future_to_url[future]
           try:
               data = future.result()
           except Exception as exc:
               print('%r generated an exception: %s' % (url, exc))
           else:
               print('%r page is %d bytes' % (url, len(data)))


InterpreterPoolExecutor
-----------------------

The :class:`InterpreterPoolExecutor` class uses a pool of interpreters
to execute calls asynchronously.  It is a :class:`ThreadPoolExecutor`
subclass, which means each worker is running in its own thread.
The difference here is that each worker has its own interpreter,
and runs each task using that interpreter.

The biggest benefit to using interpreters instead of only threads
is true multi-core parallelism.  Each interpreter has its own
:term:`Global Interpreter Lock <global interpreter lock>`, so code
running in one interpreter can run on one CPU core, while code in
another interpreter runs unblocked on a different core.

The tradeoff is that writing concurrent code for use with multiple
interpreters can take extra effort.  However, this is because it
forces you to be deliberate about how and when interpreters interact,
and to be explicit about what data is shared between interpreters.
This results in several benefits that help balance the extra effort,
including true multi-core parallelism,  For example, code written
this way can make it easier to reason about concurrency.  Another
major benefit is that you don't have to deal with several of the
big pain points of using threads, like nrace conditions.

Each worker's interpreter is isolated from all the other interpreters.
"Isolated" means each interpreter has its own runtime state and
operates completely independently.  For example, if you redirect
:data:`sys.stdout` in one interpreter, it will not be automatically
redirected any other interpreter.  If you import a module in one
interpreter, it is not automatically imported in any other.  You
would need to import the module separately in interpreter where
you need it.  In fact, each module imported in an interpreter is
a completely separate object from the same module in a different
interpreter, including :mod:`sys`, :mod:`builtins`,
and even ``__main__``.

Isolation means a mutable object, or other data, cannot be used
by more than one interpreter at the same time.  That effectively means
interpreters cannot actually share such objects or data.  Instead,
each interpreter must have its own copy, and you will have to
synchronize any changes between the copies manually.  Immutable
objects and data, like the builtin singletons, strings, and tuples
of immutable objects, don't have these limitations.

Communicating and synchronizing between interpreters is most effectively
done using dedicated tools, like those proposed in :pep:`734`.  One less
efficient alternative is to serialize with :mod:`pickle` and then send
the bytes over a shared :mod:`socket <socket>` or
:func:`pipe <os.pipe>`.

.. class:: InterpreterPoolExecutor(max_workers=None, thread_name_prefix='', initializer=None, initargs=(), shared=None)

   A :class:`ThreadPoolExecutor` subclass that executes calls asynchronously
   using a pool of at most *max_workers* threads.  Each thread runs
   tasks in its own interpreter.  The worker interpreters are isolated
   from each other, which means each has its own runtime state and that
   they can't share any mutable objects or other data.  Each interpreter
   has its own :term:`Global Interpreter Lock <global interpreter lock>`,
   which means code run with this executor has true multi-core parallelism.

   The optional *initializer* and *initargs* arguments have the same
   meaning as for :class:`!ThreadPoolExecutor`: the initializer is run
   when each worker is created, though in this case it is run.in
   the worker's interpreter.  The executor serializes the *initializer*
   and *initargs* using :mod:`pickle` when sending them to the worker's
   interpreter.

   .. note::
      Functions defined in the ``__main__`` module cannot be pickled
      and thus cannot be used.

   .. note::
      The executor may replace uncaught exceptions from *initializer*
      with :class:`~concurrent.futures.interpreter.ExecutionFailed`.

   The optional *shared* argument is a :class:`dict` of objects that all
   interpreters in the pool share.  The *shared* items are added to each
   interpreter's ``__main__`` module.  Not all objects are shareable.
   Shareable objects include the builtin singletons, :class:`str`
   and :class:`bytes`, and :class:`memoryview`.  See :pep:`734`
   for more info.

   Other caveats from parent :class:`ThreadPoolExecutor` apply here.

:meth:`~Executor.submit` and :meth:`~Executor.map` work like normal,
except the worker serializes the callable and arguments using
:mod:`pickle` when sending them to its interpreter.  The worker
likewise serializes the return value when sending it back.

.. note::
   Functions defined in the ``__main__`` module cannot be pickled
   and thus cannot be used.

When a worker's current task raises an uncaught exception, the worker
always tries to preserve the exception as-is.  If that is successful
then it also sets the ``__cause__`` to a corresponding
:class:`~concurrent.futures.interpreter.ExecutionFailed`
instance, which contains a summary of the original exception.
In the uncommon case that the worker is not able to preserve the
original as-is then it directly preserves the corresponding
:class:`~concurrent.futures.interpreter.ExecutionFailed`
instance instead.


ProcessPoolExecutor
-------------------

The :class:`ProcessPoolExecutor` class is an :class:`Executor` subclass that
uses a pool of processes to execute calls asynchronously.
:class:`ProcessPoolExecutor` uses the :mod:`multiprocessing` module, which
allows it to side-step the :term:`Global Interpreter Lock
<global interpreter lock>` but also means that
only picklable objects can be executed and returned.

The ``__main__`` module must be importable by worker subprocesses. This means
that :class:`ProcessPoolExecutor` will not work in the interactive interpreter.

Calling :class:`Executor` or :class:`Future` methods from a callable submitted
to a :class:`ProcessPoolExecutor` will result in deadlock.

.. class:: ProcessPoolExecutor(max_workers=None, mp_context=None, initializer=None, initargs=(), max_tasks_per_child=None)

   An :class:`Executor` subclass that executes calls asynchronously using a pool
   of at most *max_workers* processes.  If *max_workers* is ``None`` or not
   given, it will default to :func:`os.process_cpu_count`.
   If *max_workers* is less than or equal to ``0``, then a :exc:`ValueError`
   will be raised.
   On Windows, *max_workers* must be less than or equal to ``61``. If it is not
   then :exc:`ValueError` will be raised. If *max_workers* is ``None``, then
   the default chosen will be at most ``61``, even if more processors are
   available.
   *mp_context* can be a :mod:`multiprocessing` context or ``None``. It will be
   used to launch the workers. If *mp_context* is ``None`` or not given, the
   default :mod:`multiprocessing` context is used.
   See :ref:`multiprocessing-start-methods`.

   *initializer* is an optional callable that is called at the start of
   each worker process; *initargs* is a tuple of arguments passed to the
   initializer.  Should *initializer* raise an exception, all currently
   pending jobs will raise a :exc:`~concurrent.futures.process.BrokenProcessPool`,
   as well as any attempt to submit more jobs to the pool.

   *max_tasks_per_child* is an optional argument that specifies the maximum
   number of tasks a single process can execute before it will exit and be
   replaced with a fresh worker process. By default *max_tasks_per_child* is
   ``None`` which means worker processes will live as long as the pool. When
   a max is specified, the "spawn" multiprocessing start method will be used by
   default in absence of a *mp_context* parameter. This feature is incompatible
   with the "fork" start method.

   .. versionchanged:: 3.3
      When one of the worker processes terminates abruptly, a
      :exc:`~concurrent.futures.process.BrokenProcessPool` error is now raised.
      Previously, behaviour
      was undefined but operations on the executor or its futures would often
      freeze or deadlock.

   .. versionchanged:: 3.7
      The *mp_context* argument was added to allow users to control the
      start_method for worker processes created by the pool.

      Added the *initializer* and *initargs* arguments.

   .. versionchanged:: 3.11
      The *max_tasks_per_child* argument was added to allow users to
      control the lifetime of workers in the pool.

   .. versionchanged:: 3.12
      On POSIX systems, if your application has multiple threads and the
      :mod:`multiprocessing` context uses the ``"fork"`` start method:
      The :func:`os.fork` function called internally to spawn workers may raise a
      :exc:`DeprecationWarning`. Pass a *mp_context* configured to use a
      different start method. See the :func:`os.fork` documentation for
      further explanation.

   .. versionchanged:: 3.13
      *max_workers* uses :func:`os.process_cpu_count` by default, instead of
      :func:`os.cpu_count`.

   .. versionchanged:: 3.14
      The default process start method (see
      :ref:`multiprocessing-start-methods`) changed away from *fork*. If you
      require the *fork* start method for :class:`ProcessPoolExecutor` you must
      explicitly pass ``mp_context=multiprocessing.get_context("fork")``.

.. _processpoolexecutor-example:

ProcessPoolExecutor Example
~~~~~~~~~~~~~~~~~~~~~~~~~~~
::

   import concurrent.futures
   import math

   PRIMES = [
       112272535095293,
       112582705942171,
       112272535095293,
       115280095190773,
       115797848077099,
       1099726899285419]

   def is_prime(n):
       if n < 2:
           return False
       if n == 2:
           return True
       if n % 2 == 0:
           return False

       sqrt_n = int(math.floor(math.sqrt(n)))
       for i in range(3, sqrt_n + 1, 2):
           if n % i == 0:
               return False
       return True

   def main():
       with concurrent.futures.ProcessPoolExecutor() as executor:
           for number, prime in zip(PRIMES, executor.map(is_prime, PRIMES)):
               print('%d is prime: %s' % (number, prime))

   if __name__ == '__main__':
       main()


Future Objects
--------------

The :class:`Future` class encapsulates the asynchronous execution of a callable.
:class:`Future` instances are created by :meth:`Executor.submit`.

.. class:: Future

   Encapsulates the asynchronous execution of a callable.  :class:`Future`
   instances are created by :meth:`Executor.submit` and should not be created
   directly except for testing.

   .. method:: cancel()

      Attempt to cancel the call.  If the call is currently being executed or
      finished running and cannot be cancelled then the method will return
      ``False``, otherwise the call will be cancelled and the method will
      return ``True``.

   .. method:: cancelled()

      Return ``True`` if the call was successfully cancelled.

   .. method:: running()

      Return ``True`` if the call is currently being executed and cannot be
      cancelled.

   .. method:: done()

      Return ``True`` if the call was successfully cancelled or finished
      running.

   .. method:: result(timeout=None)

      Return the value returned by the call. If the call hasn't yet completed
      then this method will wait up to *timeout* seconds.  If the call hasn't
      completed in *timeout* seconds, then a
      :exc:`TimeoutError` will be raised. *timeout* can be
      an int or float.  If *timeout* is not specified or ``None``, there is no
      limit to the wait time.

      If the future is cancelled before completing then :exc:`.CancelledError`
      will be raised.

      If the call raised an exception, this method will raise the same exception.

   .. method:: exception(timeout=None)

      Return the exception raised by the call.  If the call hasn't yet
      completed then this method will wait up to *timeout* seconds.  If the
      call hasn't completed in *timeout* seconds, then a
      :exc:`TimeoutError` will be raised.  *timeout* can be
      an int or float.  If *timeout* is not specified or ``None``, there is no
      limit to the wait time.

      If the future is cancelled before completing then :exc:`.CancelledError`
      will be raised.

      If the call completed without raising, ``None`` is returned.

   .. method:: add_done_callback(fn)

      Attaches the callable *fn* to the future.  *fn* will be called, with the
      future as its only argument, when the future is cancelled or finishes
      running.

      Added callables are called in the order that they were added and are
      always called in a thread belonging to the process that added them.  If
      the callable raises an :exc:`Exception` subclass, it will be logged and
      ignored.  If the callable raises a :exc:`BaseException` subclass, the
      behavior is undefined.

      If the future has already completed or been cancelled, *fn* will be
      called immediately.

   The following :class:`Future` methods are meant for use in unit tests and
   :class:`Executor` implementations.

   .. method:: set_running_or_notify_cancel()

      This method should only be called by :class:`Executor` implementations
      before executing the work associated with the :class:`Future` and by unit
      tests.

      If the method returns ``False`` then the :class:`Future` was cancelled,
      i.e. :meth:`Future.cancel` was called and returned ``True``.  Any threads
      waiting on the :class:`Future` completing (i.e. through
      :func:`as_completed` or :func:`wait`) will be woken up.

      If the method returns ``True`` then the :class:`Future` was not cancelled
      and has been put in the running state, i.e. calls to
      :meth:`Future.running` will return ``True``.

      This method can only be called once and cannot be called after
      :meth:`Future.set_result` or :meth:`Future.set_exception` have been
      called.

   .. method:: set_result(result)

      Sets the result of the work associated with the :class:`Future` to
      *result*.

      This method should only be used by :class:`Executor` implementations and
      unit tests.

      .. versionchanged:: 3.8
         This method raises
         :exc:`concurrent.futures.InvalidStateError` if the :class:`Future` is
         already done.

   .. method:: set_exception(exception)

      Sets the result of the work associated with the :class:`Future` to the
      :class:`Exception` *exception*.

      This method should only be used by :class:`Executor` implementations and
      unit tests.

      .. versionchanged:: 3.8
         This method raises
         :exc:`concurrent.futures.InvalidStateError` if the :class:`Future` is
         already done.

Module Functions
----------------

.. function:: wait(fs, timeout=None, return_when=ALL_COMPLETED)

   Wait for the :class:`Future` instances (possibly created by different
   :class:`Executor` instances) given by *fs* to complete. Duplicate futures
   given to *fs* are removed and will be returned only once. Returns a named
   2-tuple of sets.  The first set, named ``done``, contains the futures that
   completed (finished or cancelled futures) before the wait completed.  The
   second set, named ``not_done``, contains the futures that did not complete
   (pending or running futures).

   *timeout* can be used to control the maximum number of seconds to wait before
   returning.  *timeout* can be an int or float.  If *timeout* is not specified
   or ``None``, there is no limit to the wait time.

   *return_when* indicates when this function should return.  It must be one of
   the following constants:

   .. list-table::
      :header-rows: 1

      * - Constant
        - Description

      * - .. data:: FIRST_COMPLETED
        - The function will return when any future finishes or is cancelled.

      * - .. data:: FIRST_EXCEPTION
        - The function will return when any future finishes by raising an
          exception. If no future raises an exception
          then it is equivalent to :const:`ALL_COMPLETED`.

      * - .. data:: ALL_COMPLETED
        - The function will return when all futures finish or are cancelled.

.. function:: as_completed(fs, timeout=None)

   Returns an iterator over the :class:`Future` instances (possibly created by
   different :class:`Executor` instances) given by *fs* that yields futures as
   they complete (finished or cancelled futures). Any futures given by *fs* that
   are duplicated will be returned once. Any futures that completed before
   :func:`as_completed` is called will be yielded first.  The returned iterator
   raises a :exc:`TimeoutError` if :meth:`~iterator.__next__`
   is called and the result isn't available after *timeout* seconds from the
   original call to :func:`as_completed`.  *timeout* can be an int or float. If
   *timeout* is not specified or ``None``, there is no limit to the wait time.


.. seealso::

   :pep:`3148` -- futures - execute computations asynchronously
      The proposal which described this feature for inclusion in the Python
      standard library.


Exception classes
-----------------

.. currentmodule:: concurrent.futures

.. exception:: CancelledError

   Raised when a future is cancelled.

.. exception:: TimeoutError

   A deprecated alias of :exc:`TimeoutError`,
   raised when a future operation exceeds the given timeout.

   .. versionchanged:: 3.11

      This class was made an alias of :exc:`TimeoutError`.


.. exception:: BrokenExecutor

   Derived from :exc:`RuntimeError`, this exception class is raised
   when an executor is broken for some reason, and cannot be used
   to submit or execute new tasks.

   .. versionadded:: 3.7

.. exception:: InvalidStateError

   Raised when an operation is performed on a future that is not allowed
   in the current state.

   .. versionadded:: 3.8

.. currentmodule:: concurrent.futures.thread

.. exception:: BrokenThreadPool

   Derived from :exc:`~concurrent.futures.BrokenExecutor`, this exception
   class is raised when one of the workers
   of a :class:`~concurrent.futures.ThreadPoolExecutor`
   has failed initializing.

   .. versionadded:: 3.7

.. currentmodule:: concurrent.futures.interpreter

.. exception:: BrokenInterpreterPool

   Derived from :exc:`~concurrent.futures.thread.BrokenThreadPool`,
   this exception class is raised when one of the workers
   of a :class:`~concurrent.futures.InterpreterPoolExecutor`
   has failed initializing.

   .. versionadded:: next

.. exception:: ExecutionFailed

   Raised from :class:`~concurrent.futures.InterpreterPoolExecutor` when
   the given initializer fails or from
   :meth:`~concurrent.futures.Executor.submit` when there's an uncaught
   exception from the submitted task.

   .. versionadded:: next

.. currentmodule:: concurrent.futures.process

.. exception:: BrokenProcessPool

   Derived from :exc:`~concurrent.futures.BrokenExecutor` (formerly
   :exc:`RuntimeError`), this exception class is raised when one of the
   workers of a :class:`~concurrent.futures.ProcessPoolExecutor`
   has terminated in a non-clean
   fashion (for example, if it was killed from the outside).

   .. versionadded:: 3.3